Adaptive visual servoing of robots with uncertain gravity regressor and Jacobian matrices

摘要

Most research so far in adaptive control of robots has assumed that models of gravity regressor matrix and kinematics are known exactly. To overcome this drawback, we propose in this paper, a vision-based setpoint control law with uncertainties in gravity regressor matrix and kinematics. Sufficient conditions for choosing the feedback gains, gravity regressor and Jacobian matrix are presented to guarantee the stability. Simulation results of a 3-link planar robot manipulator are presented to illustrate the performance of the proposed controller.